Hyperspectral cameras may be used effectively to analyze spectral response of structural surfaces, enabling the detection of contaminants, moisture, foreign materials, etc. Systems including these hyperspectral cameras may be used during a manufacturing process for in-process evaluations of composite structures. However, typical hyperspectral cameras require the collection of very large amounts of spectral data at every pixel, or point on a surface of the composite structures. The large amounts of data must be sorted through and analyzed to obtain relevant information. Consequently, image processing time associated with three-dimensional spectral data collected from imaging arrays during a manufacturing process may be slow.
Because of the time involved in image processing, manufacturing goals and inspection goals may not be tenable while taking advantage of typical hyperspectroscopy systems and methods. Further, significant computer resources and cameras including complex hyperspectral imaging arrays are required for typical analysis methods. The hyperspectral cameras may also be susceptible to signal noise produced by ambient light and other sources. Other disadvantages may exist.